January 2018
Intermediate to advanced
470 pages
11h 9m
English
Content preview from Scala Machine Learning Projects
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Analyzing and Predicting Telecommunication Churn
In this chapter, we will develop a machine learning (ML) project to analyze and predict whether a customer is likely to cancel the subscription to his telecommunication contract or not. In addition, we'll do some preliminary analysis of the data and take a closer look at what types of customer features are typically responsible for such a churn.
Widely used classification algorithms, such as decision trees, random forest, logistic regression, and Support Vector Machines (SVMs) will be used for analyzing and making the prediction. By the end, readers will be able to choose the best model to use for a production-ready environment.
In a nutshell, we will learn the following topics throughout this ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.